[Feature] Support ExPose for SMPL-X estimation (#201)

- Expose body + hand + face
- smplx datasets
- expressive mesh estimator

Co-authored-by: shizhelun <[email protected]>

Author: Coach257

README.md

@@ -84,6 +84,7 @@ Supported methods:
 - [x] [PARE](https://pare.is.tue.mpg.de/) (ICCV'2021)
 - [x] [DeciWatch](https://ailingzeng.site/deciwatch) (arXiv'2022)
 - [x] [SmoothNet](https://ailingzeng.site/smoothnet) (arXiv'2022)
+- [x] [ExPose](https://expose.is.tue.mpg.de) (ECCV'2020)
 
 </details>
 
@@ -109,6 +110,9 @@ Supported datasets:
 - [x] [PoseTrack18](https://posetrack.net/users/download.php) (CVPR'2018)
 - [x] [SURREAL](https://www.di.ens.fr/willow/research/surreal/data/) (CVPR'2017)
 - [x] [UP3D](https://files.is.tuebingen.mpg.de/classner/up/) (CVPR'2017)
+- [x] [FreiHand](https://lmb.informatik.uni-freiburg.de/projects/freihand/) (ICCV'2019)
+- [x] [EHF](https://smpl-x.is.tue.mpg.de/) (CVPR'2019)
+- [x] [Stirling/ESRC-Face3D](http://pics.psych.stir.ac.uk/ESRC/index.htm) (FG'2018)
 
 </details>
 

README_CN.md

@@ -84,6 +84,7 @@ https://user-images.githubusercontent.com/62529255/144362861-e794b404-c48f-4ebe-
 - [x] [PARE](https://pare.is.tue.mpg.de/) (ICCV'2021)
 - [x] [DeciWatch](https://ailingzeng.site/deciwatch) (arXiv'2022)
 - [x] [SmoothNet](https://ailingzeng.site/smoothnet) (arXiv'2022)
+- [x] [ExPose](https://expose.is.tue.mpg.de) (ECCV'2020)
 
 </details>
 
@@ -109,6 +110,9 @@ https://user-images.githubusercontent.com/62529255/144362861-e794b404-c48f-4ebe-
 - [x] [PoseTrack18](https://posetrack.net/users/download.php) (CVPR'2018)
 - [x] [SURREAL](https://www.di.ens.fr/willow/research/surreal/data/) (CVPR'2017)
 - [x] [UP3D](https://files.is.tuebingen.mpg.de/classner/up/) (CVPR'2017)
+- [x] [FreiHand](https://lmb.informatik.uni-freiburg.de/projects/freihand/) (ICCV'2019)
+- [x] [EHF](https://smpl-x.is.tue.mpg.de/) (CVPR'2019)
+- [x] [Stirling/ESRC-Face3D](http://pics.psych.stir.ac.uk/ESRC/index.htm) (FG'2018)
 
 </details>
 

configs/expose/README.md

@@ -0,0 +1,141 @@
+#ExPose
+
+## Introduction
+We provide the config files for ExPose: [Monocular Expressive Body Regression through Body-Driven Attention](https://arxiv.org/abs/2008.09062).
+
+
+```BibTeX
+@inproceedings{ExPose:2020,
+  title = {Monocular Expressive Body Regression through Body-Driven Attention},
+  author = {Choutas, Vasileios and Pavlakos, Georgios and Bolkart, Timo and Tzionas, Dimitrios and Black, Michael J.},
+  booktitle = {European Conference on Computer Vision (ECCV)},
+  pages = {20--40},
+  year = {2020},
+  url = {https://expose.is.tue.mpg.de}
+}
+```
+
+## Notes
+
+- [SMPLX](https://smpl-x.is.tue.mpg.de/) v1.1 is used in our experiments.
+- [FLAME](https://flame.is.tue.mpg.de/) 2019 is used in our experiments.
+- [MANO](https://mano.is.tue.mpg.de/) v1.2 is used in our experiments.
+- [SMPL](https://smpl.is.tue.mpg.de/) v1.0 is used for body evaluation on 3DPW.
+- [all_means.pkl](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmhuman3d/data/body_models/smplx/all_means.pkl?versionId=CAEQRBiBgIChyabujhgiIDQwNDMzNzlmM2U4ZTQzNWY5NjUxMmU4ZGQ4NGMwNmIx)
+- [J_regressor_h36m.npy](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmhuman3d/models/J_regressor_h36m.npy?versionId=CAEQHhiBgIDE6c3V6xciIDdjYzE3MzQ4MmU4MzQyNmRiZDA5YTg2YTI5YWFkNjRi)
+- [MANO_SMPLX_vertex_ids.pkl](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmhuman3d/data/body_models/smplx/MANO_SMPLX_vertex_ids.pkl?versionId=CAEQRBiBgIDjx9v4jhgiIDJjZjhiMWI1ZGRmMTRmMTI5MDVkMzJkMWUyYTQxZDk2)
+- [shape_mean.npy](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmhuman3d/data/body_models/smplx/shape_mean.npy?versionId=CAEQRBiBgIDqwKbujhgiIGM4OTIxMWM3MDNiNzQxN2RiOTRjNDIwZTNiMzdmMDVi)
+- [SMPL-X__FLAME_vertex_ids.npy](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmhuman3d/data/body_models/smplx/SMPL-X__FLAME_vertex_ids.npy?versionId=CAEQRBiBgMDUyNv4jhgiIDBlYzNkOTI2YzFlZjRmZWZiZTJkM2IwZGZhZjg4NzE5)
+- [SMPLX_to_J14.npy](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmhuman3d/data/body_models/smplx/SMPLX_to_J14.npy?versionId=CAEQRBiBgMDd26fujhgiIDQ3ODhmOGJhMzhhMzQ2M2Y4MTRlNDcxY2VjNmUzY2Qy)
+- [flame_dynamic_embedding.npy](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmhuman3d/data/body_models/smplx/flame_dynamic_embedding.npy?versionId=CAEQRBiBgMCn4abujhgiIDBmNmEzYTBiZmIzYjQ5NTg4MmVhZGRjYTYwNWU2MGRk)
+- [flame_static_embedding.npy](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmhuman3d/data/body_models/smplx/flame_static_embedding.pkl?versionId=CAEQRBiBgMCAxqbujhgiIGIzMTRiZjZkZjRhMDQ4NzA5YmU2YjQyMTNmYmQ5OWI5)
+- [ExPose_curated_fits](https://expose.is.tue.mpg.de)
+- [spin_in_smplx](https://expose.is.tue.mpg.de)
+- [ffhq_annotations.npz](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmhuman3d/datasets/ffhq_annotations.npz?versionId=CAEQRBiBgMCO46zvjhgiIDJhNDhlYTM2N2NmYjRmM2I4NWI2NDY0ZWM4NjExMzhm) We run [RingNet](https://ringnet.is.tue.mpg.de/) on FFHQ and then fitting to FAN 2D landmarks by [flame-fitting](https://github.com/HavenFeng/photometric_optimization).
+
+As for pretrained model (hrnet_hmr_expose_body.pth). You can download it from [here](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmhuman3d/models/expose/body/hrnet_hmr_expose_body-d7db2e53_20220708.pth?versionId=CAEQRBiBgMDFt6zujhgiIDMxODBkODE4ZTI5NjQ1OTRiN2I0MDM4NWMwOTA1NTFm) and change the path of pretrained model in the config.
+You can also pretrain the model using [hrnet_hmr_expose_body.py](hrnet_hmr_expose_body.py).
+
+As for pretrained model (resnet18_hmr_expose_face.pth). You can download it from [here](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmhuman3d/models/expose/face/resnet18_hmr_expose_face-aca68aad_20220708.pth?versionId=CAEQRBiBgMCbvbbujhgiIGMxY2RlMjUyMGY4MjRmMDhiM2VkM2VhNWU4Y2ZjODZi) and change the path of pretrained model in the config.
+You can also pretrain the model using [resnet18_hmr_expose_face.py](resnet18_hmr_expose_face.py).
+
+As for pretrained model (resnet18_hmr_expose_hand.pth). You can download it from [here](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmhuman3d/models/expose/hand/resnet18_hmr_expose_hand-c6cf0236_20220708.pth?versionId=CAEQRBiBgIDvqbbujhgiIGFiZTI3YmFkOTMyMTQxZWNiYjQxYzU0NjM0N2U1ZGVh) and change the path of pretrained model in the config.
+You can also pretrain the model using [resnet18_hmr_expose_hand.py](resnet18_hmr_expose_hand.py).
+
+Download the above resources and arrange them in the following file structure:
+
+```text
+mmhuman3d
+├── mmhuman3d
+├── docs
+├── tests
+├── tools
+├── configs
+└── data
+    ├── body_models
+    │   ├── all_means.pkl
+    │   ├── J_regressor_h36m.npy
+    │   ├── flame
+    │   │   ├── FLAME_NEUTRAL.pkl
+    │   │   ├── flame_dynamic_embedding.npy
+    │   │   └── flame_static_embedding.npy
+    │   ├── mano
+    │   │   └── MANO_RIGHT.pkl
+    │   ├── smpl
+    │   │   ├── SMPL_FEMALE.pkl
+    │   │   ├── SMPL_MALE.pkl
+    │   │   └── SMPL_NEUTRAL.pkl
+    │   └── smplx
+    │       ├── all_means.pkl
+    │       ├── MANO_SMPLX_vertex_ids.pkl
+    │       ├── shape_mean.npy
+    │       ├── SMPL-X__FLAME_vertex_ids.npy
+    │       ├── SMPLX_to_J14.npy
+    │       └── SMPLX_NEUTRAL.pkl
+    ├── pretrained_models
+    │   ├── hrnet_pretrain.pth
+    │   ├── resnet18.pth
+    │   ├── hrnet_hmr_expose_body.pth
+    │   ├── resnet18_hmr_expose_face.pth
+    │   └── resnet18_hmr_expose_hand.pth
+    ├── preprocessed_datasets
+    │   ├── curated_fits_train.npz
+    │   ├── ehf_val.npz
+    │   ├── ffhq_flame_train.npz
+    │   ├── freihand_test.npz
+    │   ├── freihand_train.npz
+    │   ├── freihand_val.npz
+    │   ├── h36m_smplx_train.npz
+    │   ├── pw3d_test.npz
+    │   ├── spin_smplx_train.npz
+    │   └── stirling_ESRC3D_HQ.npz
+    └── datasets
+        ├── 3DPW
+        ├── coco
+        ├── EHF
+        ├── ExPose_curated_fits
+        │   └── train.npz
+        ├── ffhq
+        │   ├── ffhq_annotations.npz
+        │   └── ffhq_global_images_1024
+        ├── FreiHand
+        ├── h36m
+        ├── lsp
+        │   ├── lsp_dataset_original
+        │   └── lspet
+        ├── mpii
+        ├── spin_in_smplx
+        │   ├── coco.npz
+        │   ├── lsp.npz
+        │   ├── lspet.npz
+        │   └── mpii.npz
+        └── stirling
+            ├── annotations
+            ├── F_3D_N
+            ├── M_3D_N
+            └── Subset_2D_FG2018
+```
+
+## Results and Models
+
+We evaluate hrnet_hmr_expose_body on 3DPW. Values are MPJPE/PA-MPJPE.
+
+| Config | 3DPW | Download |
+|:------:|:-------:|:------:|
+| [hrnet_hmr_expose_body.py](hrnet_hmr_expose_body.py) | 92.59 / 60.43 | [model](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmhuman3d/models/expose/body/hrnet_hmr_expose_body-d7db2e53_20220708.pth?versionId=CAEQRBiBgMDFt6zujhgiIDMxODBkODE4ZTI5NjQ1OTRiN2I0MDM4NWMwOTA1NTFm) | [log](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmhuman3d/models/expose/body/20220704_005929.log?versionId=CAEQRBiBgMDCt6zujhgiIGJiYzY0ODdlMGZlMjRjYmZhZDc5YTY2YzM0OTk0NDc3) |
+
+
+We evaluate resnet18_hmr_expose_face on Stirling/ESRC 3D. Values are 3DRMSE.
+| Config | Stirling/ESRC 3D | Download |
+|:------:|:-------:|:------:|
+| [resnet18_hmr_expose_face.py](resnet18_hmr_expose_face.py) | 2.40 | [model](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmhuman3d/models/expose/face/resnet18_hmr_expose_face-aca68aad_20220708.pth?versionId=CAEQRBiBgMCbvbbujhgiIGMxY2RlMjUyMGY4MjRmMDhiM2VkM2VhNWU4Y2ZjODZi) | [log](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmhuman3d/models/expose/face/20220630_111340.log?versionId=CAEQRBiBgICFtLbujhgiIGUzYmEyOGU3N2ZkOTRkNDM5OTIyODZiOWQ1MzJiMWZj) |
+
+We evaluate resnet18_hmr_expose_hand on FreiHand. Values are PA-MPJPE/PA-PVE.
+| Config | FreiHand | Download |
+|:------:|:-------:|:------:|
+| [resnet18_hmr_expose_hand.py](resnet18_hmr_expose_hand.py) | 10.03 / 9.61 | [model](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmhuman3d/models/expose/hand/resnet18_hmr_expose_hand-c6cf0236_20220708.pth?versionId=CAEQRBiBgIDvqbbujhgiIGFiZTI3YmFkOTMyMTQxZWNiYjQxYzU0NjM0N2U1ZGVh) | [log](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmhuman3d/models/expose/hand/20220630_110254.log?versionId=CAEQRBiBgMCSuLbujhgiIDlmNDdhODg2MjA2NzQ1Njg5MTBlNWM1NDIxY2QyZmM2) |
+
+We evaluate ExPose on EHF. Values are BODY PA-MPJPE/RIGHT_HAND PA-MPJPE/LEFT_HAND PA-MPJPE/PA-PVE/RIGHT_HAND PA-PVE/LEFT_HAND PA-PVE/FACE PA-PVE.
+| Config | EHF | Download |
+|:------:|:-------:|:------:|
+| [expose.py](expose.py) | 55.70 / 14.6 / 14.4/ 56.65 / 14.6 / 14.5 / 6.90 | [model](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmhuman3d/models/expose/expose/expose-d9d5dbf7_20220708.pth?versionId=CAEQRBiBgMC8vbbujhgiIDg0NWUyM2ZiZGY3MzQ0YmI5YjFjYTA0Y2Q5NDE3MDEw)